code: def test_train_map(self):
      seed = jax.random.PRNGKey(20231018)
      x_train, y_train = util.load_fake_dataset()
  
      autobnn = estimators.AutoBnnMapEstimator(
          model_name="linear_plus_periodic",
          likelihood_model="normal_likelihood_logistic_noise",
          seed=seed,
          width=5,
          num_particles=8,
          num_iters=100,
      )
      self.assertFalse(autobnn.check_is_fitted())
      autobnn.fit(x_train, y_train)
      self.assertTrue(autobnn.check_is_fitted())
      self.assertEqual(autobnn.diagnostics_["loss"].shape, (8, 100))
      lo, mid, hi = autobnn.predict_quantiles(x_train)
      np.testing.assert_array_less(lo, mid)
      np.testing.assert_array_less(mid, hi)
      self.assertEqual(
          autobnn.summary(),
          "\n".join(["(Periodic(period=12.00)#Linear)"] * 8),
      )
  
file_path: probability/tensorflow_probability/python/experimental/autobnn/estimators_test.py
imports: import jax
  import numpy
  from tensorflow_probability.python.experimental.autobnn import estimators
  from tensorflow_probability.python.experimental.autobnn import util
  from tensorflow_probability.python.internal import test_util
label_desc: Use image node_id 1 for calling the AutoBNNTest obj's underlying member method code with example usage: obj.test_train_map() without return types